- Dive into company data to identify sources and features that will drive business objectives.
- Design data infrastructures architecture for ingestion of real-time and batch data streaming using cloud native services
- Work in interdisciplinary teams that combine technical, business and data science competencies that deliver work in waterfall or agile software development lifecycle methodologies.
- Architect, Design and Build the applications and its CICD pipelines using cloud services.
- Investigate all reported problems/errors & initiate amendments & testing so that the system can operate correctly & efficiently.
- Deploy and monitor Machine Learning Models in production environment.
- Develop and monitor REST API end points for Machine Learning Models deployment.
- Develop analytics dashboards and communicate its findings using PowerBI/Tableau.
- Setup and monitor cloud infrastructure's security and network settings.
- Have strong technical background in Python development.
- Experience in using cloud native data lake, data warehouse and databases services like Azure Data Lake, Azure Blob Storage, Azure Cosmos DB, AWS S3, AWS RedShift, etc.
- Experience in deploying Machine Learning Models using Docker/Kubernetes into production.
- Experience with ETL and data streaming pipeline like Kafka, Informatica, Talend, Azure Data Factory, Azure Synapse, AWS Kinesis, etc.
- Experience in developing API end points using Web Framework like Django or cloud serverless services like AWS API Gateway and AWS Lambda.
- Experience in setup CI/CD pipeline and familiar with the DevOps tools like Azure DevOps, Travis CI, Ansible, etc.
- Experience in developing analytics dashboard using PowerBI/Tableau.
- Strong working knowledge in Linux and shell scripting.
Licence No: 12C6060